• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.25-32
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• 2010

The paper proposes a hierarchical fault detection method for the high voltage equipment using a microphone array which detects the location of fault and the thermal imaging and CCD cameras which verifies the fault and stores the image, respectively. There are partial arc discharges on the faulty insulators, which generates a specific pattern of sound. Detecting the signal using the microphone array, the location of the faulty insulator can be estimated. The 6th band-pass filter was applied to remove noise signal from wind or external influence. When the mobile robot carries the thermal and CCD cameras to the possible place of the fault insulator, the fault insulators or power transmission wires can be detected by the thermal images, which are caused by the aging or natural erosion. Finally, the CCD camera captures the image of the fault insulator for the record. The detection scheme of fault location using the microphone array and the thermal images have been proved to be effective through the real experiments. As a result of this research, it becomes possible to use a mobile robot with the integrated sensors to detect the fault insulators instead of a human being.

• Journal of Sensor Science and Technology
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• v.5 no.2
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• pp.37-46
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• 1996

This paper describes a system that can be used to recognize unknown materials regardless of the change in ambient temperature by using temperature response curve fitting and fuzzy neural network(FNN). There are problems with a recognition system which utilize temperature responses. It requires too many memories to store the vast temperature response data and it has to be filtered to remove the noise which occurs in experiments. Thus, this paper proposes a practical method using curve fitting to remove the above problems of memories and noise. Also, the FNN is proposed to overcome the problem caused by the change of ambient temperature. Using the FNN which is learned by temperature responses on fixed ambient temperatures and known thermal conductivity, the thermal conductivity of the material can be inferred on various ambient temperatures. So the material can be recognized via its thermal conductivity.

• Publications of The Korean Astronomical Society
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• v.11 no.1
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• pp.109-123
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• 1996

We have developed a 5GHz continuum receiver system. The receiver is a direct type receiver. In order to reduce the noise due to the fluctuation of the gain in the amplifiers, the system employs the Dicke switching method. We made the 5GHz low-noise amplifier and the bandpass filter. The low-noise amplifier gives ${\sim}35dB$ gain and has ${\sim}210K$ noise temperature. The bandpass filter has a passband between 4.3 and 5.4GHz. We also made switch driver, video amplifiers, phase detector, and integrator. Using a 1.8 meter offset parabolic antenna, we measured the efficiency of the system. Since the antenna does not have a driver to track objects, observations were performed with the antenna fixed. The measured noise temperature of the system is ${\sim}650K$. From the observation of the blank sky, noise level was measured. It was found that the systematic noise(${\sim}0.5K$: peak to peak value) is much larger than the thermal noise. The systematic noise is possibly related to the stability of the DC power supplied to the receiver system. Besides the noise of the system, it was found that the airplanes are the very serious noise sources. We measured the radio flux of the Sun using the developed system. The observed radio flux of the Sun is ${\sim}10^6Jy$, which is close to the known value of the quiet Sun. The test observation of the Sun shows that the angular beam size of the antenna is ${\sim}2.2^{\circ}$.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.569-582
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• 2023

Lead-acid Battery is the oldest rechargeable battery system and has maintained its position in the rechargeable battery field. The battery causes thermal runaway for various reasons, which can lead to major accidents. Therefore, preventing thermal runaway is a key part of the battery management system. Recently, research is underway to categorize thermal runaway battery cells into machine learning. In this paper, we present a thermal runaway hazard cell detection and verification algorithm using DBSCAN and statistical method. An experiment was conducted to classify thermal runaway hazard cells using only the resistance values as measured by the Battery Management System (BMS). The results demonstrated the efficacy of the proposed algorithms in accurately classifying thermal runaway cells. Furthermore, the proposed algorithm was able to classify thermal runaway cells between thermal runaway hazard cells and cells containing noise. Additionally, the thermal runaway hazard cells were early detected through the optimization of DBSCAN parameters using a grid search approach.

• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.684-701
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• 2016

The Gaussian process model (GPM) is a flexible surrogate model that can be used for nonparametric regression for multivariate problems. A unique feature of the GPM is that a prediction variance is automatically provided with the regression function. In this paper, we estimate the safety margin of a nuclear power plant by performing regression on the output of best-estimate simulations of a large-break loss-of-coolant accident with sampling of safety system configuration, sequence timing, technical specifications, and thermal hydraulic parameter uncertainties. The key aspect of our approach is that the GPM regression is only performed on the dominant input variables, the safety injection flow rate and the delay time for AC powered pumps to start representing sequence timing uncertainty, providing a predictive model for the peak clad temperature during a reflood phase. Other uncertainties are interpreted as contributors to the measurement noise of the code output and are implicitly treated in the GPM in the noise variance term, providing local uncertainty bounds for the peak clad temperature. We discuss the applicability of the foregoing method to reduce the use of conservative assumptions in best estimate plus uncertainty (BEPU) and Level 1 probabilistic safety assessment (PSA) success criteria definitions while dealing with a large number of uncertainties.

• Journal of Sensor Science and Technology
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• v.9 no.6
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• pp.440-447
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• 2000

This paper describes a practical system to classify material temperature responses by composition of curve fitting and neuro-fuzzy inference. There are problems with a classification system which utilizes temperature responses. It requires too much time to approach the steady state of temperature response and it has to be filtered to remove the noise which occurs in experiments. Thus, this paper proposes a practical method using curve fitting only for transient state to remove the above problems of time and noise. Using the neuro-fuzzy system, the thermal conductivity of the material can be inferred on various ambient temperatures. So the material can be classified via its inferred thermal conductivity. To realize the system, we designed a contact sensor which has a similar structure with human finger, implemented a hardware system, and developed a classification software of curve fitting and neuro-fuzzy algorithm.

• Korean Journal of Computational Design and Engineering
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• v.21 no.3
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• pp.224-233
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• 2016

We propose a new method to visualize 3D models for FDM (Fused Deposition. Modeling) printing that appearance of the printed results can be predicted more realistically as that the efficiency of the modeling-printing process can be improved. The layered nature of horizontal slicing and the vibratory nozzle movements of customer-level FDM 3D printers leaving the characteristic patterns of noisy stripes on the surfaces of printed objects make difficulties in prediction of printed result in company with the thermal contraction of filament material. First, our method analyses the G-codes generated by common slicers to obtain proper outlines and take advantages of a modified version of Perlin noise based texturing method for rendering efficiency and enough number of control parameters on the visual details. The results show improved rendering details of pre-visualization of FDM printing.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.5
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• pp.366-371
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• 2012

In this paper, fabricated by MEMS uncooled micro-bolometer detector for the study in the infrared sensitivity enhancement. Absorption layer SiOx-Metal series MDTF (metal-dielectric thin film) by high absorption rate and has a high thermal coefficient of resistance, low noise characteristics were implemented. Then MDTF were made in a vacuum deposition method. And MDTF for the analysis of the physical properties of silicon wafers were fabricated, TCR (temperature coefficient of resistance) value was made in order to measure the glass wafer and FT-IR (Fourier Transform Infrared spectroscopy) values were made in order to measure the germanium window. The analyzed results of MDTF -3 [%/K] has more characteristics of the TCR. And 8~12 um wavelength region close to 70% in the absorption characteristic.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.4
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• pp.463-473
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• 2011

The warm shrink fitting process is generally used to assemble automobile transmission parts (shaft/gear). But the fitting process can cause the dimensions of addendum and dedendum of the gear to change with respect to the fitting interference and the profile of the gear. As a result, there may be additional noise and vibration between gears. To address these problems, we analyzed the warm shrink fitting process according to process parameters; the fitting interference between the outer diameter of the shaft and the inner diameter of the gear, the inner diameter of the gear, addendum and dedendum of the gear, the heating temperature. In this study, a closed form equation for predicting the amount of deformation of addendum and dedendum in the R-direction was proposed. And the FEA method to analyze the cooling process was proposed for thermal-structural-thermal coupled field analysis of the warm shrink fitting process (heating-fitting-cooling process).

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.4
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• pp.391-396
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• 2023

Recently, as power and electronic devices have increased in frequency and capacity, it has become a major concern to protect electronic circuits and electronic components used in these devices from abnormal voltages such as various surges and pulse noise. To respond to variously rated voltages applied to power electronic devices, the rated voltages of various varistors can be obtained by controlling the size of internal particles of the varistor or controlling the number of layers of the varistor. During bonding, the problem of unbalanced thermal runaway occurring between the electrode and the varistor interface causes degradation of the varistor and shortens its life of the varistor. In this study, to solve the problem of unbalanced heat distribution of stacked varistors to adjust the operating voltage, the contents of the ZnO-based varistor composition were 96 wt% ZnO, 1 mol% Sb₂O₃, 1 mol% Bi₂O₃, 0.5 mol% CoO, 0.5 mol% MnO, and 1 mol% TiO₂. A multi-layered ZnO varistor was modeled by bonding a single varistor with a composition in three layers according to the operating voltage. The thermal distribution of the triple-layered ZnO varistor was analyzed for the thermal runaway phenomenon that occurred during varistor operation using the finite element method according to Comsol 5.2.